• ETRI Journal
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• v.27 no.3
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• pp.273-279
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• 2005

Toward code division multiple access (CDMA) communications and data protection, we propose and analyze pseudorandom noise (PN) sequences generated from a 2-dimensional array structure of shift-registers. For any positive integers m and n, we construct PN sequences of period $2^{mm}-1$ using an $m{\times}n$ array of registers and show that we can generate all shifted PN sequences as required by IS-95x with the proper linear combination of available sequences.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10b
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• pp.782-785
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• 1988

A two-dimensional positioning system by use of an M-array is proposed. An M-array pattern, which is known as one of the two-dimensional pseudorandom array, is attached on an object to be positioned. The M-array pattern is observed by a TV camera and crosscorrelated with the reference M-array. The maximum of the two-dimensional crosscorrelation function is sought by two-dimensional servo system. This method of positioning can be used in very noisy circumstances.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.7-12
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• 1994

This paper describes an outline of pseudorandom M-sequence and its applications to measurement and control engineering. At first, generation and properties of M-sequence is briefly described and then its applications to delay time measurement, information transmission by use of M-array, two dimensional positioning, fault detection of logical circuit, fault detection of RAM, linear and nonlinear system identification.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.221-225
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• 1998

This paper is to present a method for recognizing an image of a tracking object by processing the image from a camera, whose attitude is controlled in inertial space with inertial co-ordinate system. In order to recognize an object, a pseudo-random M-array is attached on the object and it is observed by the camera which is controlled on inertial coordinate basis by inertial stabilization unit. When the attitude of the camera is changed, the observed image of M-array is transformed by use of affine transformation to the image in inertial coordinate system. Taking the cross-correlation function between the affine-transformed image and the original image, we can recognize the object. As parameters of the attitude of the camera, we used the azimuth angle of camera, which is de-fected by gyroscope of an inertial sensor, and elevation an91e of camera which is calculated from the gravitational acceleration detected by servo accelerometer.